Wealth and Air Pollution Identified as Key Predictors of Autism Rates in U.S. States
A recent study published in Psychological Reports has identified socioeconomic status (SES) and air pollution as the strongest predictors of Autism Spectrum Disorder (ASD) prevalence across the United States. The research, conducted by Stewart J. H. McCann, analyzed data from 2017 and found that these two factors together accounted for 55.7% of the variance in state-level ASD rates.
Using a two-predictor model, the study revealed that SES alone explained 32.9% of the variance in autism rates, with a beta coefficient of .73 and a significance level of p < .001. Air pollution, measured as particulate matter (PM2.5), contributed an additional 22.8% to the variance, with a beta coefficient of .50 and a similar level of significance.
The study also noted a Pearson correlation of .57 between SES and ASD rates, indicating a strong overall relationship. The correlation between PM2.5 and ASD rates was weaker, at .28, and approached statistical significance with a p-value of .051.
This research aligns with previous findings from the CDC, which reported an increase in ASD prevalence, estimating that about 1 in 31 children aged 8 were identified with ASD in 2022. However, the CDC data did not analyze SES at the state level. Earlier studies have also shown a consistent increase in ASD prevalence with higher SES, with differences of about 4.0 per 1,000 children between high- and low-SES areas.